This package contains 2 functions,plot_geo_time_value() and plot_gif_geo_time_value(), used to draw input data on a map of France.
Draws input data values on a series of maps of France (Matplotlib subplots), 1 per year.
Saves output to output.pdf
| Parameter | Description |
|---|---|
| x | longitude (list) |
| y | latitudes (list) |
| year | years to draw (list) |
| value | values to draw (dataframe or numpy array) |
| proj | projection methods (string) |
| axs | matplotilb axes returned by the matplotlib.subplot() function |
| name | names of the places to draw (vector) |
| hue | meaning of the values (string) |
plot_gif_geo_time_value(x, y, year, value, proj='mercator', method='gif', fig=None, ax=None, name=[], hue='', **kwargs)
Makes a video of the evolution of input data values of the years on a map of France (matplotlib Axe object).
Saves output to output.'method'
| Parameter | Description |
|---|---|
| x | longitude (list) |
| y | latitudes (list) |
| year | years to draw (list) |
| value | values to draw (dataframe or numpy array) |
| proj | projection methods (string) |
| method | file output format (string) |
| fig | matplotilb figure to draw on |
| axs | matplotilb axes returned by the matplotlib.subplot() function |
| name | names of the places to draw (vector) |
| hue | meaning of the values (string) |
Example of project using this package : https://github.com/gabsens/Python-for-Data-Scientists-ENSAE/blob/master/Devoir/IREP%20et%20devoir.ipynb
fig, axs = plt.subplots(2, 2, figsize=(20,20), subplot_kw={'projection': ccrs.Mercator()})
# data longiture/latitude
x, y = data['LLX'], data['LLY']
years = range(2004, 2008)
years_str = [str(year) for year in years]
values = data[[colname for colname in data.columns.values if colname[-4:] in years_str]].astype('float')
plot_geo_time_value(x, y, year=years, value=values, proj='mercator', axs=axs, hue='produits dangereux')`
fig, ax = plt.subplots(figsize=(10,10), subplot_kw={'projection': ccrs.Mercator()})
# data longiture/latitude
x, y = data['LLX'], data['LLY']
years = range(2003, 2018)
years_str = [str(year) for year in years]
values = data[[colname for colname in data.columns.values if colname[-4:] in years_str]].astype('float')
plot_gif_geo_time_value(x, y, value=values, year=years, fig=fig, ax=ax, proj='mercator', method='gif', hue='produits dangereux')
